The number of triangles (i.e., three-vertex clique) is a key metric to extract insights for a wide range of graph applications, such as, anomaly detection [1]}, [2]},
community detection [3]}, [4]}, [5]}, [6]},
and robustness analysis [7]}. For more thorough studies about the applications surrounding triangle counting, we refer the readers to recent surveys [8]}, [9]}, [10]}.
Further, triangle counting is also a basic primitive for an array of graph algorithms, e.g., clustering coefficient [11]}, k-truss [12]}, [13]}, [14]},
and transitivity ratio calculation [15]}. Ultimately, the significance of triangle counting is pronounced by the GraphChallenge competition [16]}, where
participants
are ranked by how fast they perform triangle counting on a collection of graph datasets.
